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Matching unorganized points data under different viewpoints based on improved evolution algorithm
基于改进的差异演化算法的多视角离散数据配准

Keywords: unorganized points,data matching,ICP,differential evolution
离散数据
,数据配准,最近点迭代,差异演化

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Abstract:

In order to align partly overlapped data clouds measured from different viewpoints and with greate difference in initial position, this paper proposed a detecting method based on differential evolution and ICP algorithm. Firstly, roughly registrated data clouds with differential evolution algorithm method and then employed ICP algorithm method in the accuracy registration.In differential evolution, used quaternion method to decrease the individual numbers of revolution space and accordingly adapted the selection operation, to avoid premature convergence and improve optimizing speed, adaptively adjusted the probabilities of crossover and mutation by means of adaptive algorithm.Some examples prove the method is effective and efficient for aligning large number of three dimension clouds data.

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